class_docstr: Keeps track of a running mean for seen states.
  
  The filter will be used to normalize observations and will be 
  online updated according to the seen observations of all actors.
code: def __init__(self, shape, demean=True, destd=True, clip=10.0):
      self.shape = shape
      self.demean = demean
      self.destd = destd
      self.clip = clip
      self.rs = RunningStat(shape)
      # In distributed rollouts, each worker sees different states.
      # The buffer is used to keep track of deltas amongst all the
      # observation filters.
  
      self.buffer = RunningStat(shape)
  
imports: import numpy
label_desc: Use image node_id 1 to create a new MeanStdFilter object from inherited base classes: Filter with example: obj = MeanStdFilter(shape, demean, destd, clip)